Target Tracking Research In Indoor Complex Environment Based On Wireless Sensor Network

Wireless Sensor Networks (WSN) is considered as one of the most significant emerging technologies as an Integration of multidisciplinary research focus.Target tracking is an important application area of WSN which has been widely used in the military environment,health care,transportation,etc.This thesis introduces several particle filter algorithm,summarizes in detail the unique tracking wireless sensor network solutions and evaluation standards.On this basis,the distance measurement model is amended.Aimed at complex electromagnetic indoor environment,a target tracking experimental system based on Gaussian particle filter is designed.In indoor environment,the distance measurement model is different for various complex factors,such as blocking material,refraction,and multipath effect.Ranging error is relatively large if the exisiting empirical model is used,then the tracking accuracy is reduced.This paper designs an RSSI ranging model parameters identification experiment by using TI’s CC2431Development Kit.Based on the measured data in the experiment,least squares fitting method is used to fit the RSSI ranging model in order to give the optimal estimate of the model parameters.A target tracking experiment system based on Gaussian particle filter is designed on the basis of the distance model.The system collecting the value of RSSI of the tracking reference node that blind node send.Use the Gaussian particale filter tracking algorithm and substitute RSSI distance measurement model into the algorithm as the measurement model.Finally,estimate the state of the mobile blind node and display the trajectory of the target node on the host computer.The results showed that,in a range of2.5m distance,a moving target can be tracked in real time by using Gaussian Particle Filter which is based on the model of RSSI distance measurement.The tracking accuracy is maintained in the range of0.5m.